IS WORK OVER?

Automation index

How much of a Forest ranger’s job can AI already do?

A log and a GIS come earlier. Walking the forest and stopping a fire do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Forest ranger

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Logs, GIS and penalty files.
Estimate

No public source provides a precise figure. This is our estimate.

16%32%+5.1
Patrol, poaching and fires.
Estimate

No public source provides a precise figure. This is our estimate.

22%10%+2.2
Neighbours, shepherds and councils.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Sampling, paths and signage.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Duties, weather and terrain.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Not arriving late to a column of smoke.
Estimate

No public source provides a precise figure. This is our estimate.

14%14%+2
Total100%18%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Logs, GIS and penalty files
  • Patrol, poaching and fires
  • Neighbours, shepherds and councils
  • Sampling, paths and signage
  • Duties, weather and terrain
  • Not arriving late to a column of smoke
  • agente forestal
  • agente medioambiental
  • forest ranger

Sources for this job· O*NET 33-3031.00· ESCO/ISCO 5419

Logistics analyst

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Costs, OTIF and the dashboard.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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